Modified Third Harmonic Injection Modulation for Voltage Balancing in Multilevel Inverters

To provide balanced energy extraction from different DC sources in a multilevel inverter, a new modulation method based on harmonic injection is proposed in this paper. The proposed method is inspired by the well-known 3rd harmonic injection method and can be implemented in any multilevel topology. Since the proposed method uses the sources sequentially and does not need to make any of the sources bypassed, it particularly suits binary multilevel inverters. The proposed method is studied with sinusoidal and triangular injected waveforms to compare their effectiveness for different output voltages. The functionality of the proposed method is approved by simulation results and the improvements in the case of balanced energy extraction is compared with the conventional method

Sliding Carrier SPWM for Voltage Balancing in Multilevel Inverters

A new modulation method to realize equalized energy extraction from the cells in a multilevel inverter (MLI) is proposed in this paper. This method is based on changing the location of the carrier waveform corresponded to each cell within one cycle, to control the delivered energy value by the cell. In order to recognize time points in which the transitions will take place between carrier waveforms, an energy study is carried out. The procedure provides the scheme for the first quarter cycle and for the second quarter cycle a sophisticated swapping will be used to make energy extraction even more equal. Since the proposed method is based on energy study, it is more effective compared to the methods trying to bring equalization by time interval balancing. The sliding carrier method is particularly useful for the MLIs with higher number of levels. Simulation results prove approximately 98% reduction in the variance value for the delivered energy values of different cells

Use of TerraSAR-X data to retrieve soil moisture over bare soil agricultural fields

The retrieval of the bare soil moisture content from TerraSAR-X data is discussed using empirical approaches. Two cases were evaluated: 1) one image at low or high incidence angle and 2) two images, one at low incidence and one at high incidence. This study shows by using three databases collected between 2008 and 2010 over two study sites in France (Orgeval and Villamblain) that TerraSAR-X is a good remote sensing tool for the retrieving of surface soilmoisture with accuracy of about 3% (rmse).Moreover, the accuracy of the soil moisture estimate does not improve when two incidence angles (26◦–28◦ or 50◦–52◦) are used instead of only one. When compared with the result obtained with a high incidence angle (50◦–52◦), the use of low incidence angle (26◦–28◦) does not enable a significant improvement in estimating soil moisture (about 1%)

Remote Sensing of Soil

Remote sensing has shown a high potential in soil characteristics retrieving in the last three decades. Different methodologies have been proposed for the estimation of soil parameters, based on different remote sensing sensors and techniques (passive and active)

An N-port system model for multiwinding transformer based multilevel converters in DC-autotransformer configuration

This paper proposes a time-domain modelling approach for a multi-winding transformer-based multilevel DC/DC converter. Within previous research, multi-winding transformers have been modeled using cantilever models. These models, while simple, have no direct intuitive interpretation. Furthermore, they do not include currents circulating within each individual module and external load currents affecting only some of the modules at the same time. In this paper, a DC/DC converter model that includes the transformer as N-port network with magnetization and stray inductance and conduction losses is proposed. The model is verified using simulations showing both accurate predictions of both, circulating currents within each module and load currents affecting multiple modules

A DC-Autotransformer based Multilevel Inverter for Automotive Applications.

This paper proposes a novel multilevel inverter for automotive applications. The topology consists of a modular DCDC converter and a tap selector, where the DC-DC converter provides several DC-output levels and the tap selector produces an AC signal by choosing different DC-output signals from the DC-DC converter. To produce the DC-levels, the DC-DC converter consists of a modular structure where the modules are connected in series. The novelty is that the modules are connected both, magnetically in the AC-domain and electrically in the DCdomain. Due to the usage of low power switches in the modules, the proposed structure provides high efficiency. Furthermore, the DC-DC converter is capable of self-balancing its modules and thus does not require large capacitors which yields a high power density. A prototype of the proposed converter is built and simulation, as well as experimental results, are used to verify the findings

Going further with smaller EVs: System-level battery range, emissions and charging infrastructure analysis

Electric vehicles are a necessary part of a zero-carbon future. However, one in five motorists worldwide depend on small petrol motorcycles for their transport needs — vehicles for which no satisfactory low-carbon substitute exists. Meanwhile, the rise in electric car ownership is not reducing GHG emissions as much as often thought, due to the significant emissions from producing ever-larger batteries. Both problems can be solved by uncovering the mechanisms of long distance EV travel, beyond battery range, where the interaction with recharging infrastructure governs vehicle performance. This study develops a new model for journeys involving multiple run-recharge cycles and introduces a novel metric for EV performance — Day Range. Not only does this allow a direct comparison between a wide variety of vehicle and infrastructure options but, by further manipulating the formulae, high level trends can be observed and specific quantitative guidelines extracted. In vehicle design, a strong emphasis on efficiency and recharge rates can drastically reduce both in-use and embodied energy while matching the touring performance of a conventional, resource intensive, heavy battery car. Meanwhile, the recharging network can be developed to better support this lower energy use. Taking the example of the UK motorway network, charge rates up to only 100kW should be installed with the focus instead falling on reliably reducing chargepoint intervals at least as far as the existing target of 28 miles, and ideally much further. In doing so, required battery capacity can be reduced from the 60kWh+ currently seen as necessary to as little as 25kWh. The resulting vehicles not only consume less energy in motion but emit far less greenhouse gases during manufacture and will cost less to produce, allowing a much wider uptake of electric vehicles than possible under the existing, energy intensive battery vehicle touring paradigm

A Sphere Decoding Algorithm for Multistep Sequential Model Predictive Control

This paper investigates the combination of two model predictive control concepts, sequential model predictive control and long-horizon model predictive control for power electronics. To achieve sequential model predictive control, the optimization problem is split into two subproblems: The first one summarizes all control goals which linearly depend on the system inputs. Sequential model predictive control generally requires to obtain more than one solution for the first subproblem. Due to the mixed-integer nature of finite control set model predictive control power electronics a special sphere decoder is therefore proposed within the paper. The second subproblem consists of all those control goals which depend nonlinearly on the system inputs and is solved by an exhaustive search. The effectiveness of the proposed method is validated via numerical simulations at different scenarios on a three-level neutral point clamped permanent magnet synchronous generator wind turbine system and compared to other long-horizon model predictive control methods

Nanoscale intermittent contact-scanning electrochemical microscopy

A major theme in scanning electrochemical microscopy (SECM) is a methodology for nanoscale imaging with distance control and positional feedback of the tip. We report the expansion of intermittent contact (IC)-SECM to the nanoscale, using disk-type Pt nanoelectrodes prepared using the laser-puller sealing method. The Pt was exposed using a focused ion beam milling procedure to cut the end of the electrode to a well-defined glass sheath radius, which could also be used to reshape the tips to reduce the size of the glass sheath. This produced nanoelectrodes that were slightly recessed, which was optimal for IC-SECM on the nanoscale, as it served to protect the active part of the tip. A combination of finite element method simulations, steady-state voltammetry and scanning electron microscopy for the measurement of critical dimensions, was used to estimate Pt recession depth. With this knowledge, the tip-substrate alignment could be further estimated by tip approach curve measurements. IC-SECM has been implemented by using a piezo-bender actuator for the detection of damping of the oscillation amplitude of the tip, when IC occurs, which was used as a tip-position feedback mechanism. The piezo-bender actuator improves significantly on the performance of our previous setup for IC-SECM, as the force acting on the sample due to the tip is greatly reduced, allowing studies with more delicate tips. The capability of IC-SECM is illustrated with studies of a model electrode (metal/glass) substrate